Lemes and Pino 9 used Kohonen’s self-organizing map (SOM) 10 to place five-dimensional features of elements (i.e. Precisely, the observed physicochemical properties of elements are mapped onto regular grid points in a two-dimensional latent space such that the configured chemical symbols adequately capture the underlying periodicity and similarity of the elements. From this approach, building a periodic table can be viewed as an unsupervised learning task. ![]() However, a recent study has attempted to redesign the periodic table using computer intelligence-machine learning 9. The periodic tables proposed so far have been products of human intelligence. The structures of these proposed tables have not been limited to the two-dimensional tabular form, but also spiral, loop, or three-dimensional pyramid forms 6– 8. Regardless, the design of the periodic table continues to evolve, and hundreds of periodic tables have been proposed in the last 150 years 4, 5. Despite the subsequent emergence of significant discoveries 2, 3, including the modern quantum mechanical theory of the atomic structure, Mendeleev’s achievement is still the de facto standard. Inspired by this discovery, he constructed the first periodic table. When the elements were arranged according to their atomic weight, Mendeleev noticed an apparent periodicity and an increasing regularity. At that time, about 60 elements and their few chemical properties were known. The prototype of the current periodic table was first presented by Mendeleev in 1869 1. The periodic table is a tabular arrangement of elements such that the periodic patterns of their physical and chemical properties are clearly understood. We further showed what the PTG learned from the element data and how the element features, such as melting point and electronegativity, are compressed to the lower-dimensional latent spaces. The PTG autonomously produced various arrangements of chemical symbols, which organized a two-dimensional array such as Mendeleev’s periodic table or three-dimensional spiral table according to the underlying periodicity in the given data. The PTG is an unsupervised machine learning algorithm based on the generative topographic mapping, which can automate the translation of high-dimensional data into a tabular form with varying layouts on-demand. ![]() To achieve this goal, we developed a periodic table generator (PTG). In this study, we seek to answer the question of whether machine learning can reproduce or recreate the periodic table by using observed physicochemical properties of the elements. In terms of data science, his achievement can be viewed as a successful example of feature embedding based on human cognition: chemical properties of all known elements at that time were compressed onto the two-dimensional grid system for a tabular display. In 1869, the first draft of the periodic table was published by Russian chemist Dmitri Mendeleev.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |